Children on the autism spectrum update their behaviour in response to a volatile environment

Abstract

Typical adults can track reward probabilities across trials to estimate the volatility of the environment and use this information to modify their learning rate (Behrens et al., 2007). In a stable environment, it is advantageous to take account of outcomes over many trials, whereas in a volatile environment, recent experience should be more strongly weighted than distant experience. Recent predictive coding accounts of autism propose that autistic individuals will demonstrate atypical updating of their behaviour in response to the statistics of the reward environment. To rigorously test this hypothesis, we administered a developmentally appropriate version of Behrens et al.'s (2007) task to 34 cognitively able children on the autism spectrum aged between 6 and 14 years, 32 age‐ and ability‐matched typically developing children and 19 typical adults. Participants were required to choose between a green and a blue pirate chest, each associated with a randomly determined reward value between 0 and 100 points, with a combined total of 100 points. On each trial, the reward was given for one stimulus only. In the stable condition, the ratio of the blue or green response being rewarded was fixed at 75:25. In the volatile condition, the ratio alternated between 80:20 and 20:80 every 20 trials. We estimated the learning rate for each participant by fitting a delta rule model and compared this rate across conditions and groups. All groups increased their learning rate in the volatile condition compared to the stable condition. Unexpectedly, there was no effect of group and no interaction between group and condition. Thus, autistic children used information about the statistics of the reward environment to guide their decisions to a similar extent as typically developing children and adults. These results help constrain predictive coding accounts of autism by demonstrating that autism is not characterized by uniform differences in the weighting of prediction error.

Contextual priors do not modulate action prediction in children with autism

“…However, it is worth mentioning that other studies have shown that ASD children are able to use statistical information from the environment to a similar extent as TD children. For instance, Manning et al [51] tested how ASD and TD children used reward probabilities in a decision-making task under stable or volatile contexts (i.e. fixed versus fluctuating probabilities).…”

“…Interestingly, Manning et al [51] also explored the possible link between children's anxiety and task performance. However, they did not find correlations between these aspects.…”

Increased variability but intact integration during visual navigation in Autism Spectrum Disorder

“…Unfortunately, as for many other aspects of the ASD phenotype and pathology, there is yet no clear consensus. Remarkably, both attenuated Noel et al, 2016) and intact (Pell et al, 2016;Croydon et al, 2017;Karvelis et al, 2018) priors have been reported, as well as normal (Manning et al, 2017) and abnormal Lieder et al, 2019) updating of these priors. These conflicting results may partially be due to a lack of quantification.…”

Autistic traits, but not schizotypy, predict overweighting of sensory information in Bayesian visual integration

“…However, the direction of gaze priors 23 and the light---from---above priors 24 were found to be intact. Autistic children also demonstrated intact ability to update their priors in a volatile environment in a decision---making task 25 but a follow---up study in ASD adults showed that they overestimate volatility in a changing environment 26 .…”